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Tier-1 brand, generalist Data Scientist title, and metro location increase candidate competition.
Role requires banking fraud/AML domain expertise, reducing cross-industry transferability.
Explicit 6-10 years requirement plus banking domain and technical skill mandates tighten filters.
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Own analysis of large and complex data sets to evaluate and support business strategies impacting the entire specialized analytics area.
Lead documentation of data requirements and end-to-end data processes including collection, cleaning, and exploratory data analysis using statistical models and visualization techniques.
Serve as a recognized technical authority influencing business decisions in fraud analytics, with an emphasis on risk assessment and compliance.
6-10 years of experience in a quantitative field, preferably within Financial or Credit Card industry.
Proficient in data retrieval and manipulation using tools such as SQL and Access, with strong analytical and problem-solving skills.
Bachelor’s degree required; Master’s degree preferred.
Excellent communication skills and proficiency in Microsoft Office, specifically MS Excel for analytic presentations.
Experienced in handling and analyzing large, complex data sets with expertise in fraud analytics, marketing, risk, digital, or AML fields.
Strategic thinker capable of influencing cross-functional teams and guiding data-driven business decisions in matrix environments.
Strong technical and commercial awareness with demonstrated ability to drive compliance and risk assessment in financial services.